Laser capture microdissection (LCM) is a robust and reliable technology for isolating pure populations of cells from heterogeneous tissue samples for subsequent analysis. The LCM technology integrates a laboratory microscope with a low-energy laser and transfer film in a convenient one-step, aim-and-shoot method. Generally, thin sections of tissue samples are mounted on standard glass slides employing various common methods known in the art such as fixing tissues with alcohol-based precipitation techniques. LCM is compatible with various common methods for the preparation of tissue sections.
The thin tissue sections may be stained by standard techniques such as hematoxylin and eosin, methylene green nuclear stain, fluorescence in situ hybridization, or immunohistochemistry for identification of tissue morphology and cell populations of interest. Staining the sample may or may not be required. In some cases, a marker is added to the tissue sample to adhere to a specific type of site in the tissue to render the site detectable in an image of the tissue that is captured via an acquisition system. Markers may be antibodies, drugs, or other compounds that attach or bind to the tissue component of interest and are radioactive or fluorescent or have a distinctive color or otherwise detectable. Once mounted on a substrate surface such as a standard glass slide, the transfer film is located in juxtaposition to the tissue surface. The transfer film is typically made of thermoplastic film such as ethylene-vinyl acetate. Broadband energy absorbing transfer films are described in U.S. Pat. No. 6,495,195 entitled “Broadband absorbing film for laser capture microdissection” issued to Baer et al. and hereby incorporated by reference in its entirety.
Once loaded in a LCM device, a tissue sample is viewed via a microscope and a cell or cells of interest are targeted. The laser is directed at the cell or cells of interest and pulsed to provide enough energy to transiently and locally melt the thermoplastic film and activate the transfer film in the precise focal region of the laser beam. The laser beam spot size can be adjusted so that a targeted individual cell or cluster of cells can be selected in one or more pulses of the laser. The optical system of a LCM instrument is described in U.S. Pat. No. 6,215,550 and U.S. Pat. No. 6,512,576 both entitled “Laser capture microdissection optical system” and issued to Baer et al. and both hereby incorporated by reference in its entirety.
The cell or cells in the activated region of the transfer film adhere to the transfer film and can be extracted from the remaining tissue sample with the unselected tissue remaining in contact with the glass slide. Because the thermoplastic film absorbs most of the thermal energy and the pulse lasts for a fraction of a second, no detectable damage of the biological macromolecules occurs. Once removed from the tissue sample, the selected cell or cells are subjected to appropriate extraction conditions for ensuing molecular analysis. To facility subsequent extraction steps, the transfer film can be mounted on a substrate surface that is shaped like a cap that fits a microcentrifuge tube as described in U.S. Pat. No. 6,157,446 entitled “Laser capture microdissection analysis vessel” issued to Baer et al. and hereby incorporated by reference in its entirety and in U.S. Pat. No. 5,859,699 entitled “Laser capture microdissection analysis vessel” issued to Baer et al. and hereby incorporated by reference in its entirety. A method for manufacturing a consumable is described in U.S. Pat. No. 5,985,085 entitled “Method of manufacturing consumable for laser capture microdissection” issued to Baer et al. and hereby incorporated by reference in its entirety. Laser capture microdissection is also described in U.S. Pat. No. 6,469,779 entitled “Laser capture microdissection method and apparatus” issued to Baer et al. and hereby incorporated by reference in its entirety.
By isolated only target cells from the tissue sample using LCM, researchers can immediately analyze the gene and enzyme activity of the target cells using other research tools. Such procedures as polymerase chain reaction amplification of DNA and RNA, and enzyme recovery from the tissue sample have been demonstrated. No limitations have been reported in the ability to amplify DNA or RNA from tumor cells extracted with laser capture microdissection. LCM has been particularly advantageous in identifying the differences between expression levels in normal and diseased tissues. In addition to combining LCM with several genomic and proteomic techniques to document the progression of normal cells to premalignant and metastatic cancer cells in various tissues, microdissected cells are also used in applications for gaining new insights in developmental biology.
The LCM technique has been automated as described in International Patent Publication No. WO 01/33190 entitled “Automated laser capture microdissection” to Baer et al. and hereby incorporated by reference in its entirety and in International Patent Publication No. WO 02/037159 entitled “Road map image for automated microdissection” to Baer et al. and hereby incorporated by reference in its entirety. Continued automation of the LCM process is desired. In particular, automated tissue image analysis for target cell classification for subsequent laser capture microdissection is wanting for high-throughput batch processing. This invention addresses these needs for increased automation, accurate and reliable image analysis and cell classification for LCM.
Tissue analysis and identification of a cell or a region of interest (ROI) have always been a time-consuming, laborious process. The major obstacles to the successful deployment of a high-throughput tissue analysis system are the diversity in the ROIs and cell types, the variability in staining, and the skepticism from the user community.
There exists an abundance of literature and prior art in the field of automated tissue recognition. U.S. Pat. No. 6,327,377 issued to Rutenberg, et al. entitled “Automated cytological specimen classification system and method” uses a primary detector based on thresholding of an integrated optical density (IOD), a secondary classifier that utilizes a three-layer back-propagation neural network for pattern matching, and a tertiary screener by a human operator. Another U.S. Pat. No. 6,215,892 issued to Douglas et al. entitled “Method and apparatus for automated image analysis of biological specimens” uses a color-ratio threshold as an initial detector followed by a morphology-based analysis for identifying potential ROI candidates. U.S. Pat. No. 5,987,158 issued to Meyer et al. entitled “Apparatus for automated identification of thick cell groupings on a biological specimen” takes a slightly different approach to ROI classification. After image segmentation, it uses Fisher's linear binary decision tree in series to perform object (ROI) classification.
Unfortunately, none of these patents address the core issue of how to facilitate high-throughput cell classification processing that yields robust performance through the creation and manipulation of global training databases to ease the burden on human operators. Furthermore, modern nonparametric learning algorithms for studying gene activation patterns and regulatory networks require a lot of high-quality data. This invention bridges the gap by providing a flexible, high-throughput cell classification processing chain in two complementary dimensions to improve system performance with age.